[0001] The disclosure relates to a system for collecting and using data regarding the moisture
content of crop or crop material during the haymaking process.
BACKGROUND
[0002] Hay or bale creation includes a number of individual steps, such as cutting, tedding,
raking, baling, and chemical application needed to prepare, collect, and bale the
crop material for later use. In many instances, the crop material being baled is subsequently
used for feed, being fed to farm animals and the like for nutrition and sustenance.
As such, the bale creation process attempts to maximize the level of nutrition contained
in the crop material so as to increase the level of nutrition contained in each bale.
Furthermore, the bale creation process assures the crop material is able to dry out
before it is baled to avoid mold and spoilage. Together, these two goals are generally
at odds with one another such that assisting one is typically to the detriment of
the other. For example, the crop material must be handled, such as by tedding and
raking, to help assure the crop material is properly aerated and able to dry thoroughly,
however, handling the crop material damages the individual strands and removes leaves
such that the nutritional value of the crop material is reduced. The problem with
overly handling the crop material is particularly troublesome in instances where the
crop material is already dry. As such, the bale creation process must strike a balance
between handling the crop material sufficiently to assure the crop material is dry
enough to avoid molding while limiting the handling so as not to bring down the crop's
nutritional value.
[0003] WO 2010/003421 A1 describes a method for optimizing harvesting of crop in which during a production
step (mowing, tedding, raking) the moisture of crop deposited on a field is sensed
at various locations of the field and provided to a computing system which, also based
on a weather forecast, calculates an optimized drying time before the next step of
the harvesting process is performed. These production steps are performed on the entire
field, even in case that tedding is not required where the material is sufficiently
dry.
[0004] US 2012/0109614 A1 describes a method for estimating a crop characteristic, in which crop properties
on a first field are sensed with a remote (aerial) system. These sensed data and data
from other fields, which have already been harvested, are used for estimating the
crop characteristic of the first field.
[0005] WO 2016/070195 A1 describes a method for estimating the amount of water available to plants based on
sensor values from temperature and moisture sensors disposed in an agricultural field.
[0006] DE 10 2011 100 054 A1 shows an agricultural machine with a sensor scanning the ground over a width dependent
on the width of the implement coupled to the machine.
Summary
[0007] A crop management system for tedding and raking or baling crop material positioned
on a field includes a field sensor configured to detect one or more parameters of
the crop material at multiple locations in the field and to output a signal representative
of the detected parameters at each location, and a data processor in operable communication
with the field sensor and configured to receive the signal, and where the data processor
is also configured to compile the data representative of the one or more parameters
of the crop material at the multiple locations with corresponding position data to
determine the time and location of the processing process. The data processor is configured
to determine the portions of the field requiring tedding and the portions of the field
that do not require tedding.
[0008] Data sensors, such as moisture sensors and the like, collect and monitor one or more
parameters of a material or location in space. In the present disclosure, one or more
moisture sensors are positioned over or moved across a field to detect the moisture
content in the cut crop material in a plurality of locations. The sensors then transmit
their collected data and corresponding location information to a central data processor
to compile and map the data.
[0009] Contrary to typical hay creation processes, where entire swaths of field must be
tedded, raked, and baled as a single entity based on little more than a farmer's intuition,
the data processor of the present disclosure is able to utilize the data provided
by the moisture sensors to identify particular locations within the field where the
moisture content is too high to be baled and determine the correct time and processes
needed to bring the moisture to an acceptable limit. As such, by compiling the data
provided by the one or more data sensors, only the crop material in need of tedding
and raking is handled. Therefore, relatively dry regions of the field can be left
untouched, maximizing their nutritional value, and wet regions can be handled only
as necessary until they are dry and ready for baling. Implementations of the disclosure
relate to the collection of information regarding the moisture content within the
mowed crop material at a particular field location to allow a more accurate determination
of where and when the crop material should be tedded, raked, and baled. More specifically,
one method includes receiving crop information from one or more field sensors, compiling
the crop information and location data to produce a field map, and using the field
map to at least partially dictate the parameters of the haymaking process. Furthermore,
the field map can be used to determine the most efficient time to rake the crop material
into windrows. Still further, the field map can be used to determine the most efficient
time to bale the crop material. Still further, the field map can be used to determine
the specific locations at which preservatives or other chemicals should be applied.
[0010] Other aspects of the disclosure will become apparent by consideration of the detailed
description and accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011]
- FIG. 1
- is a schematic diagram of a crop management system.
- FIG. 2
- is a block diagram of the crop management system of FIG. 1.
- FIG. 3
- is a schematic view of a field with a plurality of sensors positioned therein.
- FIG. 4
- is a schematic view of a field with a single sensor moving therethrough.
- FIG. 5
- illustrates a field map generated by the crop management system of FIG. 1.
DETAILED DESCRIPTION
[0012] FIG. 1 illustrates a crop management system 10 for detecting and monitoring the moisture
content of crop material 14 (i.e., straw, alfalfa, and the like) in a field 18 to
aid the haymaking process. More specifically, the resulting haymaking process maximizes
the nutrient value within the harvested crop material 14 by minimizing lost leaf matter
through less handling of the crop material. Furthermore, the management system 10
provides for a more efficient process by limiting the tedding and chemical application
processes to only those regions of the field 18 that require such actions. During
use, the crop management system 10 collects data regarding the moisture content in
mowed crop material 14 at specific locations in the field 18 and evaluates and/or
combines that data to at least partially direct the tedding, raking, and baling processes.
For example, the system 10 may utilize the moisture content data to direct, among
other things, the timing and location of the tedding process; the timing and location
of the raking process; the timing of the baling process; and the timing, location,
and quantity of preservatives or other chemicals applied to the crop material.
[0013] As illustrated in FIGS. 1 and 2, the system 10 includes one or more field sensors
22, a data processor 26 in operable communication with the one or more field sensors
22, and one or more user interfaces 66a, 66b, 66c in operable communication with the
data processor 26. The crop management system 10 may also include one or more farm
vehicles having tedding, raking, baling, and/or chemical application capabilities.
In the illustrated implementation, the crop management system 10 is in operable communication
with a tedding tractor 30, a raking tractor 34, and a baling tractor 38. In still
other implementations, the crop management system 10 may also be configured for retrofit
onto existing farm equipment.
[0014] The tedding tractor 30 of the present implementation includes a first drive unit
or tractor 32a with a tedding attachment 32b coupled thereto. During use, the tedding
attachment 32b uses a plurality of moving forks to aerate or "wuffle" the hay and
speed up the process of haymaking by allowing the hay to dry or cure more evenly and
quickly.
[0015] The raking tractor 34 of the present implementation includes a second drive unit
or tractor 36a with a raking attachment 36b coupled thereto. During use, the raking
attachment 36b collects the mowed crop material and combines it into windrows for
subsequent collection. The raking attachment 36b may also fluff up the hay and turn
it over to aid the drying process.
[0016] The baling tractor 38 of the present implementation includes a third drive unit or
tractor 40a with a baling attachment 40b coupled thereto. During use, the baling attachment
40b collects the crop material 14 in the windrows and compacts the material 14 into
individual bales for subsequent use.
[0017] Although not illustrated, the crop management system 10 may also include a chemical
tractor (not shown) having a chemical attachment or trailer for applying pesticides,
drying agents, fertilizer, and the like to the crop material 14.
[0018] While the present disclosure describes each of the three tractors 30, 34, 38 as separate
items, it is to be understood some tractors may be coupled to multiple attachments
and used for more than one process. Furthermore, the three tractors 30, 34, 38 may
be used simultaneously or separately, and at different times, during the haymaking
process.
[0019] Illustrated in FIGS. 1-3, each field sensor 22 of the crop management system 10 is
in operable communication with the data processor 26 and is configured to detect one
or more agricultural field parameters from the mowed crop material 14 in its general
vicinity. In the illustrated implementation, each field sensor 22 includes a moisture
sensor 42 able to determine the moisture level within the crop material 14 at a given
location. Each field sensor 22 may also include a location device or GPS 46 to determine
the location of the sensor 22 with respect to the field 18 and a transmitter 50 to
communicate the moisture and position data to the data processor 26 during use.
[0020] Illustrated in FIG. 3, a first implementation of the crop management system 10 includes
a plurality of fixed field sensors 22a-i, each positioned evenly throughout the field
18 in a substantially rectangular array. In such an implementation, the plurality
of sensors 22a-i remain in a fixed position relative to the field which allows each
individual sensor 22a-i to continuously detect the moisture level at its particular
location. Due to the stationary nature of the sensors 22a-i, the sensors may not need
a location device 46 if the location of the sensor 22a-i is predetermined. While the
sensors 22a-i of the illustrated implementation are positioned in a rectangular array;
in alternative implementations, the sensors 22a-i may be distributed over the field
18 in any pattern that provides sufficient coverage including a spiral pattern, and
the like.
[0021] Although not illustrated the fixed field sensors 22a-i may be positioned throughout
the field in a manner similar to survey markers. In other implementations, the sensors
22a-i may be buried underground at various locations throughout the field. In other
implementations, the field sensors 22a-i may be scattered over the field. In still
other implementations, the sensors 22a-i may be biodegradable. Still further, in some
implementations, the sensors 22a-i may be positioned over the entire field, while
in other implementations, the sensors 22a-i may only be positioned in certain sub-sections
or locations of the field.
[0022] Illustrated in FIG. 4, a second implementation of the crop management system 10 includes
one or more field sensors 22a that move with respect to the field 18. In such an implementation,
the single sensor 22a may cover the entire field 18 but may only provide information
regarding a single location at any one time. In such implementations, the field sensor
22a may be coupled to and move with a tractor (not shown) taking successive readings
of the moisture level of the crop material 14 shortly after it has been mowed. In
still other implementations, the field sensor 22a may be coupled to a drone or other
moveable device (not shown) to move independently of any of the tractors 30, 34, 38.
In such implementations, the sensor 22a may move in a predetermined pattern (such
as a spiral, back and forth, and the like) to provide even coverage over the entire
field 18 (see Fig. 4), or alternatively, the sensor 22a may be directed to travel
toward or around a specific location on the field 18 to provide more focused coverage.
[0023] Although not illustrated, in another implementation of the crop management system
10 a combination of both stationary sensors and movable sensors may be used. In such
implementations, the stationary sensors may provide a data regarding the entire field
while the movable sensors supplement that data as it moves across the field. As such,
the data processor 26 would take into account both data sets when determining the
specifics of the baling process.
[0024] The data processor 26 of the management system 10 includes a central processing unit
or CPU 54, a memory unit 58 in operable communication with the CPU 54, and a communication
module 62 in operable communication with the CPU 54. In the illustrated implementation,
the data processor 26 is in operable communication with the one or more field sensors
22 via the communication module 62. The data processor 26 is also in operable communication
with a plurality of remote user interfaces 66a, 66b, 66c, each of which may be associated
with a corresponding tractor 30, 34, 38. In the illustrated implementation, the communication
module 62 is a wireless system using Bluetooth, WiFi, or other similar technologies.
However, in alternative implementations, other types of communication modules, including
wired, may be used. In still other implementations, the user interfaces 66a, 66b,
66c may be stand-alone items that can be carried or temporarily installed in one of
the tractors during use.
[0025] The data processor 26 is also in operable communication with a weather input 70 able
to provide up-to-date weather forecasts of weather conditions at and around the field
18. The weather input 70 may be a signal provided by a remote source (i.e., the internet,
the national weather service, and the like) or the weather input 70 may be local,
i.e., a dedicated station built on site (not shown).
[0026] During operation of the management system 10, the CPU 54 continuously receives data
from each field sensor 22 in the form of moisture level and position data. The CPU
54 then compiles the moisture level with its associated position data to create data
points on a field map 74, or another form of 2-D representation of the moisture levels
at various locations over the entire field 18 (see Fig. 5). Depending upon the number
of sensors 22 and the manner in which the data is collected (e.g., the first or second
implementations of the field sensors 22, described above), the resolution of the resulting
field map 74 may vary. Still further, the CPU 54 may include software or other algorithms
that allow the CPU 54 to estimate the moisture levels between data points provided
by the field sensors 22, allowing for a more continuous map.
[0027] The CPU 54 is also configured to apply the compiled data to one or more algorithms
and provide outputs to the remote user interfaces 66a, 66b, 66c, generally in the
form of instructions to a user or operator regarding the parameters of the tedding,
raking, and baling processes (described below). In some implementations, the CPU 54
provides information to the user in the form of maps, textual instructions, verbal
instructions, graphical displays, operation settings and the like that allow the user
to drive or otherwise operate the necessary equipment (i.e., the tractors 30, 34,
38) in the desired manner. For example, the CPU 54 may provide the remote user interface
66a of the tedding tractor 30 with a graphical map indicating the location(s) of the
field 18 that require tedding. In other examples, the CPU 54 may provide the remote
user interface 66a of the tedding tractor 30 with verbal or visual driving instructions
or coordinates. The CPU 54 may also provide the remote user interface 66a with instructions
regarding when to engage or disengage the tedding mechanism 32b or at what settings
to operate the tedding mechanism 32b. In still other implementations, the CPU 54 may
directly control the tractors 30, 34, 38 during the haymaking process. In still other
implementations, the individual user interfaces 66a, 66b, 66c may include their own
GPS or positioning device (not shown) to allow turn-by-turn navigation instructions
or to display the relative positions of the tractor and the location in need of attention.
[0028] The CPU 54 uses the moisture data from the sensors 22 to calculate the parameters
of the tedding process. When doing so, the CPU 54 reviews the resulting moisture and
location data to determine what, if any, locations require additional assistance to
dry. After doing so, the CPU 54 calculates which locations of the field require tedding
and which locations of the field do not require tedding. In some implementations,
the CPU 54 compares the moisture data to a predetermined maximum moisture threshold.
In instances where the moisture level in one or more particular locations exceeds
the maximum moisture threshold, the CPU 54 marks that location for tedding and indicates
that information to the user via the remote user interface 66a. In other implementations,
the CPU 54 may compare the moisture data to an acceptable envelope of moisture levels
and time tables. In still other implementations, the CPU 54 may take into account
the terrain, weather, crop type, and the like to determine if a particular location
or area is in need of tedding.
[0029] Once all the locations in need of tedding are identified, the CPU 54 may also calculate
the most fuel efficient path between the locations that require tedding to help save
running time and fuel costs. In still other implementations, the CPU 54 may also use
current moisture readings and predictive models to calculate the optimal time at which
to begin the tedding process (described below). When doing so, the CPU 54 may calculate
a start time taking into account all locations that require tedding; however in alternative
implementations, the CPU 54 may calculate a unique start time for each individual
location that requires tedding. In still other implementations, the CPU 54 may use
weather data to predict the latest time one can ted the field before encountering
rain or other inclement weather.
[0030] The CPU 54 also uses the moisture data from the sensors 22 to calculate the parameters
of the raking process and the baling processes. When doing so, the CPU 54 reviews
the resulting moisture and location data to predict which locations of the field require
raking and which locations of the field do not require raking. Furthermore, the CPU
54 calculates what time(s) the raking and baling process should begin. To do this,
the CPU 54 compares the current and prior moisture and location data in the memory
unit 58 to a predetermined drying rate algorithm to produce a predictive drying model.
When creating the predictive drying model, the CPU 54 may take into account, among
other things, the grade of the land on which the crop 14 is positioned, the type of
crop 14 being harvested, and the current weather conditions via the weather input
70. The CPU 54 then applies the predictive drying model to the current moisture conditions,
using them as a starting point to predict the times at which the moisture level within
the crop material 14 will be ideal for both the raking and baling process. The ideal
time for both processes is then communicated to the user via the remote user interfaces
66b, 66c. In instances where the moisture level in the field 18 is uneven, the CPU
54 may also develop a specific path or multiple start times to take into account any
conflicting data. More specifically, the CPU 54 may divide the field into multiple
sub-units, and calculate a unique start time for each sub-unit. When dividing the
field into the sub-units, the CPU 54 may take into account numerous factors, such
as but not limited to, similar soil type, similar grade, similar shade or sun exposure,
similar terrain features, and the like.
[0031] The CPU 54 further uses the moisture data from the sensors 22 to calculate the parameters
of the chemical application process. When doing so, the CPU 54 reviews the resulting
moisture and location data to determine what, if any, locations require preservatives,
drying agents, fertilizers, or other chemical additives. In instances where the moisture
level is deemed appropriate for chemical additives, the CPU 54 marks that location
for spraying and indicates that information to the user via the remote user interface
66c in the baling tractor 38. Once all the locations in need of chemical application
have been identified, the CPU 54 may also calculate the most fuel efficient path between
each of the locations to help save running time and fuel costs. In still other implementations,
the CPU 54 may also calculate the optimal wait time before beginning the chemical
application process. In still other implementations, the CPU 54 may use the moisture
or other crop related data from the sensors 22 to determine the quantity of chemicals
that need to be applied, or the specific type of chemical that needs to be applied.
[0032] In still other implementations, the CPU 54 may use data from some processes to effect
or update the calculation of subsequent processes. For example, the CPU may use moisture
data from the sensors 22 to calculate the ideal tedding process, and then use the
results of the tedding process to update the parameters of the ideal raking and baling
process. In still other implementations, the CPU 54 may combine instructions when
sending information to a tractor 38 having multiple capabilities. For example, the
CPU 54 may combine and optimize the ideal tedding and raking processes and provide
the results to a tractor having both tedding and raking capabilities.
[0033] In still other implementations, various tractors may directly communicate with one
another to create a network of moving sensors 22a positioned at different locations
on the field. In such implementations, each moving sensor 22a can supplement the data
provided by other sensors 22a to create a single, interconnected field map 74. In
still other implementations, the various sensors (either fixed or moving) may be in
communication with a separate computer (e.g., an office computer) or online to allow
a third party to monitor the progress of the baling operation.
[0034] The CPU may also provide all of the aforementioned information to a remote location
for additional tracking, monitoring, or storing, and for real-time or future applications.
1. A crop management system (10) for processing crop material (14) positioned on a field
(18), the crop management system (10) comprising:
a field sensor (22) configured to detect one or more parameters of the crop material
(14) at multiple locations in the field (18) and to output a signal representative
of the detected parameters at each location; and
a data processor (26) in operable communication with the field sensor (22) and configured
to receive the signal, and wherein the data processor (26) is also configured to compile
the data representative of the one or more parameters of the crop material (14) at
the multiple locations with corresponding position data to determine the timing and
location of a processing process comprising tedding crop material,
characterized in that the data processor (26) is configured to determine the portions of the field (18)
requiring tedding and the portions of the field (18) that do not require tedding.
2. The crop management system (10) of claim 1, wherein the data processor (26) is configured
to combine the data representative of the one or more parameters of the crop material
(14) at the multiple locations and corresponding position data to produce data points
on a field map.
3. The crop management system (10) of claim 1 or 2, wherein the data processor (26) is
configured to combine the data representative of the one or more parameters of the
crop material (14) at the multiple locations with corresponding position data to produce
data points on a field map, and wherein the field map is displayed on a user interface.
4. The crop management system (10) of one of the claims 1 to 3, wherein the field sensor
(22) is a moisture sensor able to determine the moisture level within the crop material
(14) at each location.
5. The crop management system (10) of one of the claims 1 to 4, wherein the field sensor
(22) is movable with respect to the field (18) between a first location and a second
location different than the first location.
6. The crop management system (10) of one of the claims 1 to 5, wherein the data processor
(26) is configured to determine the time at which tedding in a particular location
should begin.
7. The crop management system (10) of one of the claims 1 to 6, wherein the field sensor
(22) is mounted on a first vehicle, and wherein the tedding is conducted by a second
vehicle different than the first vehicle.
8. The crop management system (10) of one of the claims 1 to 5, wherein the processing
process comprises raking crop material (14) and wherein the field sensor (22) is positioned
on a first vehicle, and wherein the raking process is conducted by a second vehicle
different than the first vehicle.
9. The crop management system (10) of one of the claims 1 to 5 or 8, wherein the processing
process comprises raking crop material (14) and wherein the data processor (26) is
configured to determine locations on the field (18) where raking is required, and
locations on the field (18) where raking is not required.
10. The crop management system (10) of one of the claims 1 to 5, 8 or 9, wherein the processing
process comprises raking crop material (14) and wherein the data processor (26) is
configured to determine the timing at which raking should occur at each location on
the field (18) where raking is required.
11. The crop management system (10) of one of the claims 1 to 5, wherein the processing
process comprises baling crop material (14) and wherein the field sensor (22) is positioned
on vehicle first vehicle, and wherein the baling process is conducted by a second
vehicle different than the first vehicle.
12. The crop management system (10) of one of the claims 1 to 5 or 11, wherein the processing
process comprises baling crop material (14) and wherein the data processor (26) is
configured to determine locations on the field (18) where baling is required, and
locations on the field (18) where baling is not required.
13. The crop management system (10) of one of the claims 1 to 5, 11 or 12, wherein the
processing process comprises baling crop material (14) and wherein the data processor
(26) is configured to determine the time at which baling should occur at each location
on the field (18) where baling is required.
14. The crop management system (10) of one of the claims 1 to 5, wherein the processing
process comprises applying chemicals to crop material (14) and wherein the data processor
(26) is configured to determine the quantity of chemical that needs to be applied.
1. Erntegutmanagementsystem (10) zum Verarbeiten von Erntegutmaterial (14), das auf einem
Feld (18) positioniert ist, wobei das Erntegutmanagementsystem (10) Folgendes umfasst:
einen Feldsensor (22), der konfiguriert ist, einen oder mehrere Parameter des Erntegutmaterials
(14) an mehreren Orten auf dem Feld (18) zu detektieren, und ein Signal, das die am
jedem Ort detektierten Parameter darstellt, auszugeben; und
einen Datenprozessor (26), der in Kommunikation mit dem Feldsensor (22) betrieben
werden kann, und konfiguriert ist, das Signal zu empfangen, und wobei der Datenprozessor
(26) auch konfiguriert ist, die Daten, die den einen oder die mehreren Parameter des
Erntegutmaterials (14) an den mehreren Orten darstellen, mit entsprechenden Positionsdaten
zu kombinieren, um den Zeitpunkt und den Ort eines Verarbeitungsprozesses, der das
Ausbreiten zum Trocken von Erntegutmaterial umfasst, zu bestimmen,
dadurch gekennzeichnet, dass der Datenprozessor (26) konfiguriert ist, die Abschnitte auf dem Feld (18), die das
Ausbreiten zum Trocken erfordern, und die Abschnitte auf dem Feld (18), die das Ausbreiten
zum Trocken nicht erfordern, zu bestimmen.
2. Erntegutmanagementsystem (10) nach Anspruch 1, wobei der Datenprozessor (26) konfiguriert
ist, die Daten, die den einen oder die mehreren Parameter des Erntegutmaterials (14)
an den mehreren Orten darstellen, und entsprechende Positionsdaten zu kombinieren,
um Datenpunkte auf einer Karte des Felds zu erzeugen.
3. Erntegutmanagementsystem (10) nach Anspruch 1 oder 2, wobei der Datenprozessor (26)
konfiguriert ist, die Daten, die den einen oder die mehreren Parameter des Erntegutmaterials
(14) an den mehreren orten darstellen, mit den entsprechenden Positionsdaten zu kombinieren,
um Datenpunkte auf einer Karte des Felds zu erzeugen, und wobei die Karte des Feldes
auf einer Benutzerschnittstelle angezeigt wird.
4. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 3, wobei der Feldsensor
(22) einem Feuchtigkeitssensor entspricht, der den Feuchtigkeitsgehalt in dem Erntegutmaterial
(14) an jedem Ort bestimmen kann.
5. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 4, wobei der Feldsensor
(22) bezüglich des Feldes (18) zwischen einem ersten Ort und einem zweiten Ort, der
sich von dem ersten Ort unterscheidet, bewegt werden kann.
6. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5, wobei der Datenprozessor
(26) konfiguriert ist, den Zeitpunkt zu bestimmen, an dem das Ausbreiten zum Trocken
an einem bestimmten Ort beginnen soll.
7. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 6, wobei der Feldsensor
(22) an einem ersten Fahrzeug montiert ist, und wobei das Ausbreiten zum Trocken von
einem zweiten Fahrzeug, das sich von dem ersten Fahrzeug unterscheidet, durchgeführt
wird.
8. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5, wobei der Verarbeitungsprozess
das Harken von Erntegutmaterial (14) umfasst, und wobei der Feldsensor (22) auf einem
ersten Fahrzeug positioniert ist, und wobei das Harkprozess von einem zweiten Fahrzeug,
das sich von dem ersten Fahrzeug unterscheidet, durchgeführt wird.
9. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5 oder 8, wobei der Verarbeitungsprozess
das Harken von Erntegutmaterial (14) umfasst, und wobei der Datenprozessor (26) konfiguriert
ist, Orte auf dem Feld (18), an denen Harken erforderlich ist, und Orte auf dem Feld
(18), an denen Harken nicht erforderlich ist, zu bestimmen.
10. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5, 8 oder 9, wobei der
Verarbeitungsprozess das Harken von Erntegutmaterial (14) umfasst, und wobei der Datenprozessor
(26) konfiguriert ist, den Zeitpunkt zu bestimmen, an dem Harken an jedem Ort auf
dem Feld (18), an dem Harken erforderlich ist, geschehen soll.
11. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5, wobei der Verarbeitungsprozess
das in Ballen Verpacken von Erntegutmaterial (14) umfasst, und wobei der Feldsensor
(22) auf dem ersten Fahrzeug positioniert ist, und wobei der Prozess des in Ballen
Verpackens von einen zweiten Fahrzeug, das sich von dem ersten Fahrzeug unterscheidet,
durchgeführt wird.
12. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5 oder 11, wobei der
verarbeitungsprozess das in Ballen verpacken von Erntegutmaterial (14) umfasst, und
wobei der Datenprozessor (26) konfiguriert ist, Orte auf dem Feld (18), an denen in
Ballen Verpacken erforderlich ist, und Orte auf dem Feld (18), an denen in Ballen
Verpacken nicht erforderlich ist, zu bestimmen.
13. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5, 11 oder 12, wobei
der Verarbeitungsprozess das in Ballen Verpacken von Erntegutmaterial (14) umfasst,
und wobei der Datenprozessor (26) konfiguriert ist, den Zeitpunkt zu bestimmen, an
dem das in Ballen Verpacken an jedem Ort auf dem Feld (18), an dem in Ballen Verpacken
erforderlich ist, geschehen soll.
14. Erntegutmanagementsystem (10) nach einem der Ansprüche 1 bis 5, wobei der Verarbeitungsprozess
das Anwenden von Chemikalien auf das Erntegutmaterial (14) umfasst, und wobei der
Datenprozessor (26) konfiguriert ist, die Menge der Chemikalie, die angewendet werden
muss, zu bestimmen.
1. Système (10) de gestion de récolte pour le traitement d'un produit de récolte (14)
situé sur un champ (18), le système (10) de gestion de récolte comprenant :
un capteur de champ (22) configuré pour détecter un ou plusieurs paramètres du produit
de récolte (14) à de multiples emplacements dans le champ (18) et délivrer un signal
représentant les paramètres détectés à chaque emplacement ; et
un processeur de données (26) en communication fonctionnelle avec le capteur de champ
(22) et configuré pour recevoir le signal, et le processeur de données (26) étant
également configuré pour compiler les données représentant les un ou plusieurs paramètres
du produit de récolte (14) aux multiples emplacements avec des données de position
correspondantes afin de déterminer le moment opportun et l'emplacement d'un processus
de traitement comprenant un fanage du produit de récolte,
caractérisé en ce que le processeur de données (26) est configuré pour déterminer les parties du champ
(18) nécessitant un fanage et les parties du champ (18) qui ne nécessitent pas un
fanage.
2. Système (10) de gestion de récolte selon la revendication 1, dans lequel le processeur
de données (26) est configuré pour combiner les données représentant les un ou plusieurs
paramètres du produit de récolte (14) aux multiples emplacements et des données de
position correspondantes afin de produire des points de données sur un plan du champ.
3. Système (10) de gestion de récolte selon la revendication 1 ou 2, dans lequel le processeur
de données (26) est configuré pour combiner les données représentant les un ou plusieurs
paramètres du produit de récolte (14) aux multiples emplacements à des données de
position correspondantes afin de produire des points de données sur un plan du champ,
et dans lequel le plan du champ est affiché sur une interface-utilisateur.
4. Système (10) de gestion de récolte selon l'une des revendications 1 à 3, dans lequel
le capteur de champ (22) est un capteur d'humidité apte à déterminer le niveau d'humidité
au sein du produit de récolte (14) à chaque emplacement.
5. Système (10) de gestion de récolte selon l'une des revendications 1 à 4, dans lequel
le capteur de champ (22) est mobile par rapport au champ (18) entre un premier emplacement
et un deuxième emplacement différent du premier emplacement.
6. système (10) de gestion de récolte selon l'une des revendications 1 à 5, dans lequel
le processeur de données (26) est configuré pour déterminer le moment auquel un fanage
à un emplacement particulier doit débuter.
7. Système (10) de gestion de récolte selon l'une des revendications 1 à 6, dans lequel
le capteur de champ (22) est monté sur un premier véhicule, et dans lequel le fanage
est effectué par un deuxième véhicule différent du premier véhicule.
8. Système (10) de gestion de récolte selon l'une des revendications 1 à 5, dans lequel
le processus de traitement comprend un andainage du produit de récolte (14), et dans
lequel le capteur de champ (22) est situé sur un premier véhicule, et dans lequel
le processus d'andainage est effectué par un deuxième véhicule différent du premier
véhicule.
9. Système (10) de gestion de récolte selon l'une des revendications 1 à 5 ou 8, dans
lequel le processus de traitement comprend un andainage du produit de récolte (14),
et dans lequel le processeur de données (26) est configuré pour déterminer des emplacements
sur le champ (18) où un andainage est nécessaire et des emplacements sur le champ
(18) où un andainage n'est pas nécessaire.
10. Système (10) de gestion de récolte selon l'une des revendications 1 à 5, 8 ou 9, dans
lequel le processus de traitement comprend un andainage du produit de récolte (14),
et dans lequel le processeur de données (26) est configuré pour déterminer le moment
opportun auquel un andainage doit avoir lieu à chaque emplacement sur le champ (18)
où un andainage est nécessaire.
11. Système (10) de gestion de récolte selon l'une des revendications 1 à 5, dans lequel
le processus de traitement comprend une mise en balles du produit de récolte (14),
et dans lequel le capteur de champ (22) est situé sur un premier véhicule, et dans
lequel le processus de mise en balles est effectué par un deuxième véhicule différent
du premier véhicule.
12. Système (10) de gestion de récolte selon l'une des revendications 1 à 5 ou 11, dans
lequel le processus de traitement comprend une mise en balles du produit de récolte
(14), et dans lequel le processeur de données (26) est configuré pour déterminer des
emplacements sur le champ (18) où une mise en balles est nécessaire et des emplacements
sur le champ (18) où une mise en balles n'est pas nécessaire.
13. Système (10) de gestion de récolte selon l'une des revendications 1 à 5, 11 ou 12,
dans lequel le processus de traitement comprend une mise en balles du produit de récolte
(14), et dans lequel le processeur de données (26) est configuré pour déterminer le
moment auquel une mise en balles doit avoir lieu à chaque emplacement sur le champ
(18) où une mise en balles est nécessaire.
14. Système (10) de gestion de récolte selon l'une des revendications 1 à 5, dans lequel
le processus de traitement comprend l'application de produits chimiques sur le produit
de récolte (14), et dans lequel le processeur de données (26) est configuré pour déterminer
la quantité de produit chimique devant être appliquée.